Tatevik Tadevosyan

Key Skills

Software

Data Annotation Tech

Top Subject Matter

Java programming

Sql Domain Expertise

software engineering best practices

Top Data Types

Computer Code Programming

Top Task Types

Segmentation

Classification

Prompt + Response Writing (SFT)

Computer Programming/Coding

Data Collection

Text Summarization

Question Answering

Text Generation

Object Detection

Entity (NER) Classification

RLHF

Freelancer Overview

Java & SQL Code Evaluation — AI Model Training. Brings 15+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Outlier AI and Data Annotation Tech. Education includes Master of Science, Yerevan State University (2014). AI-training focus includes data types such as Computer Code and Programming and labeling workflows including Evaluation and Rating.

Labeling Experience

Database Query & Schema Review — AI Data Quality

Data Annotation Tech

Worked as a database expert, annotating AI-generated content focused on SQL query correctness, schema design, and ETL logic. Provided authoritative assessments on query performance, normalisation, referential integrity, and scalability for training data powering AI developer tools. Flagged and explained ambiguous or misleading outputs and corrected technical documentation when needed. • Evaluated over 150 AI-generated SQL queries for performance, accuracy, and indexing. • Assessed schema designs for scalability and data integrity in enterprise workloads. • Provided detailed rationales based on real-world production experience. • Reviewed and corrected AI-generated database documentation and architectural decisions.

Worked as a database expert, annotating AI-generated content focused on SQL query correctness, schema design, and ETL logic. Provided authoritative assessments on query performance, normalisation, referential integrity, and scalability for training data powering AI developer tools. Flagged and explained ambiguous or misleading outputs and corrected technical documentation when needed. • Evaluated over 150 AI-generated SQL queries for performance, accuracy, and indexing. • Assessed schema designs for scalability and data integrity in enterprise workloads. • Provided detailed rationales based on real-world production experience. • Reviewed and corrected AI-generated database documentation and architectural decisions.

2024 - Present

Java & SQL Code Evaluation — AI Model Training

This role involved evaluating and ranking AI-generated Java and SQL code across over 200 tasks. Structured written rationales were provided for each ranking, focusing on correctness, efficiency, and production readiness. Evaluation criteria included code quality, logic errors, security, and adherence to best practices. • Maintained over 95% inter-rater agreement with gold-standard test sets. • Identified security anti-patterns and subtle logic errors in code submissions. • Wrote detailed annotation rationale including evaluation of time complexity and maintainability. • Contributed prompt rewrites to improve clarity for future annotators.

This role involved evaluating and ranking AI-generated Java and SQL code across over 200 tasks. Structured written rationales were provided for each ranking, focusing on correctness, efficiency, and production readiness. Evaluation criteria included code quality, logic errors, security, and adherence to best practices. • Maintained over 95% inter-rater agreement with gold-standard test sets. • Identified security anti-patterns and subtle logic errors in code submissions. • Wrote detailed annotation rationale including evaluation of time complexity and maintainability. • Contributed prompt rewrites to improve clarity for future annotators.

2024 - Present

Education

Work History